The broad, long-term, scientific objective of this project is to identify the behavioral and neuroanatomical factors that determine the efficacy of hand movement training after stroke. An important societal impact of achieving this objective will be the design of more effective robotic rehabilitation exercise technology, which will allow people with a stroke to increase their movement recovery beyond that possible with current approaches. The working hypothesis is that robot-assisted movement training following stroke is most effective if it promotes 1) effortful motor output, which produces 2) correlated, appropriate, sensations at the joints, muscles, and skin. Further, it is hypothesized that the amount of hand movement recovery that is possible with such robotic exercise is limited by 1) how much of the main outflow tract from the brain to the hand (i.e. the corticospinal tract, CST) is spared, 2) integrity of sensory processing, and 3) the cumulative history of previous movement practice. These hypotheses will be tested in a series of experiments with a robotic device that assists in grasping objects as the user works daily at home through a library of engaging video games.
Aim 1 is to define the benefit of correlated sensory motor activity in robot-assisted movement training. Is it beneficial to receive robot assistance that enhances the sensations experienced during training? A robotic device will help participants to practice grasping movements that they can initiate but normally could not complete, thereby intensifying joint, muscle, and cutaneous sensation. The improvements in motor function caused by this training technique will be compared with improvements when the robot does not help with movement.
Aim 2 is to define the benefit of increased motor output levels in robot-assisted movement training. Assisting movements with a robotic device as in Aim 1 can cause people to slack, decreasing their force output. By using advanced robot control software, this aim will test if training with increased relative force levels is more effective.
Aim 3 is to identify the effect of patient-specific characteristics on the effectiveness of robot-assisted training. The versions of robot-assisted training to be tested in Aims 1 and 2 presume specific neural resources for optimal effect. Is it possible to predict who will benefit most from different forms of robot-assisted hand exercise? For both Aims 1 and 2, all participants'finger rehabilitation history will be measured starting within 2 weeks of stroke onset using a wearable sensor, and sensory function and the extent of CST damage will be measured when training begins, 3-6 months later. It is hypothesized that availability of CST, sensory function, and history of previous exercise will predict the response to different forms of robotic training.

Public Health Relevance

People with hand weakness after a stroke can often recover movement ability with rehabilitation practice, but in many cases they have limited access to professional rehabilitation services because they are expensive, and thus, in the current situation, it is likely that many people do not recover as much movement ability as they could. This project will determine how to make robot-assisted movement therapy more effective than it currently is, providing a way for people with stroke to access effective, lower cost, semi-autonomous training. It will also develop a way to identify people who are most likely to benefit from robot-assisted exercise.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Research Project (R01)
Project #
5R01HD062744-04
Application #
8442318
Study Section
Musculoskeletal Rehabilitation Sciences Study Section (MRS)
Program Officer
Quatrano, Louis A
Project Start
2010-03-12
Project End
2015-02-28
Budget Start
2013-03-01
Budget End
2014-02-28
Support Year
4
Fiscal Year
2013
Total Cost
$282,875
Indirect Cost
$79,916
Name
University of California Irvine
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
046705849
City
Irvine
State
CA
Country
United States
Zip Code
92697
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Friedman, Nizan; Chan, Vicky; Reinkensmeyer, Andrea N et al. (2014) Retraining and assessing hand movement after stroke using the MusicGlove: comparison with conventional hand therapy and isometric grip training. J Neuroeng Rehabil 11:76
Taheri, Hossein; Rowe, Justin B; Gardner, David et al. (2014) Design and preliminary evaluation of the FINGER rehabilitation robot: controlling challenge and quantifying finger individuation during musical computer game play. J Neuroeng Rehabil 11:10
Friedman, Nizan; Rowe, Justin B; Reinkensmeyer, David J et al. (2014) The manumeter: a wearable device for monitoring daily use of the wrist and fingers. IEEE J Biomed Health Inform 18:1804-12
Zondervan, Daniel K; Palafox, Lorena; Hernandez, Jorge et al. (2013) The Resonating Arm Exerciser: design and pilot testing of a mechanically passive rehabilitation device that mimics robotic active assistance. J Neuroeng Rehabil 10:39
Secoli, Riccardo; Milot, Marie-Helene; Rosati, Giulio et al. (2011) Effect of visual distraction and auditory feedback on patient effort during robot-assisted movement training after stroke. J Neuroeng Rehabil 8:21